Accurate prediction of summer thermal convective systems—including their initiation, intensity, and associated hazards—remains a major challenge in operational meteorology across China. This study evaluates the utility of high-resolution temperature and humidity profiles retrieved from the Fengyun-4B (FY-4B) Geostationary Interferometric Infrared Sounder (GIIRS) for analyzing and forecasting a representative thermal convection event in Zhejiang, a coastal province in Southeast China. With significantly higher temporal and spatial resolutions than conventional radiosondes, the retrieved profiles—characterized by strong convective available potential energy (CAPE), weak convective inhibition (CIN), and elevated equivalent potential temperature (θ_e)—exhibit marked diurnal variations in thermodynamic conditions and capture pronounced moisture accumulation and vertical expansion in pre-convection environments. On this basis, this study further investigates how the assimilation of GIIRS-retrieved humidity profiles affects simulations of summer thermal convection within the China Meteorological Administration Mesoscale Model (CMA-MESO). Numerical experiments demonstrate that assimilating GIIRS-retrieved humidity profiles effectively adjusts initial moisture and thermodynamic fields, leading to improved predictions of the location and intensity of convection initiation. Multi-case experiments reveal that the assimilation of GIIRS-retrieved humidity profiles yields a 44% higher average threat score (TS) for moderate rain and above relative to experiments without such assimilation, despite considerable variability among individual cases. The results highlight the potential of FY-4B GIIRS data to enhance convective-scale forecasting and early warning systems.

Local air pollution is strongly affected by synoptic weather systems, such as fronts, troughs, low-altitude vortices, or high-altitude ridges. Nevertheless, few studies have analyzed the meteorological properties of cold or warm air masses associated to these systems and their impact on local air quality. In this study, hourly observations of fine particulate matter (diameter of up to 2.5 µm, i.e., PM_2.5), wind (V), temperature (T), pressure (P), and precipitation (R), acquired in Hangzhou in 2014–2020, were analyzed. From this analysis, weather patterns were categorized into 27 types; 89 and 94 cases illustrating the passage of warm and cold air masses over Hangzhou were identified, respectively; the influence of air mass temperature, wind speed, and wind direction on PM_2.5 concentrations and local accumulation or removal was quantified. The main results are as follows. (1) Pollution events occurred more frequently for cold than for warm air masses, but average pollutant concentration was lower for cold air masses; (2) 48% of the cold air mass cases corresponded to PM_2.5 decreases and 52% to PM_2.5 increases, with strong cold air masses ( $\mathrm{\Delta }{T}_{24\mathrm{h}}>4$°C; $|{V|}_{\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}}$ > 4 m s⁻¹) markedly reducing local pollution, but weak cold air masses ( $\mathrm{\Delta }{T}_{24\mathrm{h}}$ < 2°C; $|\mathit{V}{|}_{\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}}$ < 2 m s⁻¹) primarily inducing pollutant transport and accumulation; (3) for warm air masses, PM_2.5 accumulation or removal occurred in 60% and 40% of the cases, respectively: warm air masses ( $\mathrm{\Delta }{\mathit{T}}_{24\mathrm{h}}$ > 4°C) reduced the PM_2.5 concentration whereas weaker winds ( $|\mathit{V}{|}_{\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}}$ < 2 m s⁻¹) increased it; and (4) PM_2.5 concentration decreased sharply within 4 h after the passage of strong cold air masses, but more gradually within 14 h after the passage of strong warm air masses. These results considerably improve the current understanding of the influence of cold and warm air masses on local pollution patterns.